title: Identification of hot-spot residues in protein-protein interactions by computational docking.
abstract: BACKGROUND
  The study of protein-protein interactions is becoming increasingly important for biotechnological and therapeutic reasons. We can define two major areas therein: the structural prediction of protein-protein binding mode, and the identification of the relevant residues for the interaction (so called 'hot-spots'). These hot-spot residues have high interest since they are considered one of the possible ways of disrupting a protein-protein interaction. Unfortunately, large-scale experimental measurement of residue contribution to the binding energy, based on alanine-scanning experiments, is costly and thus data is fairly limited. Recent computational approaches for hot-spot prediction have been reported, but they usually require the structure of the complex.
  
  
  RESULTS
  We have applied here normalized interface propensity (NIP) values derived from rigid-body docking with electrostatics and desolvation scoring for the prediction of interaction hot-spots. This parameter identifies hot-spot residues on interacting proteins with predictive rates that are comparable to other existing methods (up to 80% positive predictive value), and the advantage of not requiring any prior structural knowledge of the complex.
  
  
  CONCLUSIONS
  The NIP values derived from rigid-body docking can reliably identify a number of hot-spot residues whose contribution to the interaction arises from electrostatics and desolvation effects. Our method can propose residues to guide experiments in complexes of biological or therapeutic interest, even in cases with no available 3D structure of the complex.
authors.affiliation: Life Sciences Department, Barcelona Supercomputing Center, Jordi Girona 29, 08034 Barcelona, Spain. solene.grosdidier@bsc.es
authors.forename: Solène
authors.initials: S
authors.lastname: Grosdidier
authors.forename: Juan
authors.initials: J
authors.lastname: Fernández-Recio
mesh_terms: D000596:Amino Acids / Q000378:metabolism; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D054730:Protein Interaction Domains and Motifs; D025941:Protein Interaction Mapping / Q000379:methods*; D055672:Static Electricity; D013816:Thermodynamics
chemical_list: D000596:Amino Acids